1. Field of the Disclosure
This disclosure relates generally to random number generation and, more specifically, to testing of random number generators (RNGs).
2. Description of the Related Art
Random number generators (RNGs) provide data (e.g., numbers) exhibiting randomness. RNGs may be nondeterministic, in which case subsequent random data does not depend on prior random data, or deterministic, in which case subsequent random data is determined by prior random data, but the relationship between the prior random data and the subsequent random data is sufficiently obscure for the random data to exhibit sufficient randomness for its intended application. The randomness of random data generated by a RNG makes it very difficult to determine if a RNG is working properly. Thus, for many applications, a RNG can be assumed to be working properly unless it can be determined not to be working properly. One way in which a RNG might not work properly is if the RNG becomes “stuck” and outputs the same data repeatedly. To check for such a condition, a first set of random data output by a RNG may be saved and compared to a second set of random data output by the RNG, and the comparison between the first set of random data and the second set of random data may indicate whether the first set of random data and the second set of random data are identical, in which case the improper operation of RNG may be signalled by asserting a RNG failure signal.
Since RNGs are generally quite reliable and the incidence of a “stuck” RNG is generally rare, it is problematic to test whether a circuit for testing for a “stuck” RNG will actually assert a RNG failure signal in the unlikely event of a “stuck” RNG. Uncertainty with respect to a circuit for testing for a “stuck” RNG can thus lead to uncertainty with respect to the reliability of the RNG being tested.
The use of the same reference symbols in different drawings indicates similar or identical items.